UAV-Based Coverage Path Planning for Unmanned Agricultural Vehicles

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Authors: Guangjie Xue, Engen Zhang, Guangshun An, Juan Du, Xiang Yin, Peng Zhou, Xuening Zhang
Cited by: 2
References: 26

Abstract

Accurate path planning was the prerequisite for autonomous navigation of agricultural vehicles. An Unmanned Aerial Vehicle (UAV)-based coverage path planning was developed in this research for automating guidance of agricultural vehicles and reducing the operator maneuver in the creation of navigation maps. High-resolution orthophoto maps of the field were constructed by using low-altitude UAV photogrammetry to obtain spatial information. Travel paths and working paths were automatically generated from anchor points selected by the operator under the image coordinate domain. The navigation path for unmanned agricultural vehicles was generated by Mercator projection-based conversion for the anchor pixel coordinates into latitude and longitude geographic coordinates. A Graphical User Interface (GUI) was developed for path generation, visualization, and performance evaluation, through which the proposed path planning method was implemented for autonomous agricultural vehicle navigation. Calculation accuracy tests demonstrated the mean planar coordinate error was 2.23 cm and the maximum error was 3.37 cm for path planning. Field tests showed that lateral navigation errors remained within ±5.5 cm for the unmanned high-clearance sprayer, which indicated that the developed UAV-based coverage path planning method was feasible and featured high accuracy. It provided an effective solution for achieving fully autonomous agricultural vehicle operations.

Fields of Study & Subjects

Smart Agriculture and AI Agricultural Engineering and Mechanization Plant Surface Properties and Treatments

Publication details

Journal / source
Sensors
Publisher
MDPI AG
Volume
26
Issue
3
Pages
927–927
Publication date
1 February 2026
Language
EN